Using Games to Understand and Create Randomness

Massive growth of data and communication encryption has created growing need for non-predictable, random data, needed for encryption keys creation. Need for randomness grows (nearly) linearly with growth of encryption, but randomness is very important ingredient also e.g. in quickly growing industry of game programming. Computers are deterministic devices and cannot create random results, computer procedures can generate only pseudo-random (looking random) data. For true randomness is needed some outside information - time and placement of user's keystrokes, fluctuations of current, interrupt requests in computer processor etc. But even those sources can often not comply with requests from our increasingly randomness-hunger environment of ciphered communications and data. Growing need for randomness has created a market of randomness sources; new sources are proposed constantly. These sources differ in their properties (ease of access, size of required software etc.) and in ease of estimating their quality. However, there is an easily available good source for comparing quality of randomness and also creating new randomness - computer games. The growing affectionateness of users to play digital games makes this activity very attractive for comparing quality of randomness sources and using as a source of new randomness. In the following are analyzed possibilities for investigating and extracting randomness from digital gameplay and demonstrated some experiments with simple stateless games which allow to compare existing sources of (pseudo) randomness and generate new randomness, which can be used e.g. to create cyphering keys in mobile and Internet of Things devices

Symptom control among asthmatics with a clinically significant smoking history : a cross-sectional study in Finland

Background Surprisingly little is known about asthma control among asthmatics who smoke. The aim of this cross-sectional study was to investigate asthma symptom control according to the GINA guidelines among asthmatics with a clinically significant smoking history. Methods One hundred ninety asthmatics from primary care in Finland were investigated. The patients were current or previous cigarette smokers with a history of 10 or more pack-years. They completed a questionnaire including questions on asthma symptoms and reliever use so that their level of asthma symptom control (well controlled, partly controlled, or uncontrolled) according to GINA could be determined. Results Sixty-six (34.7%) patients had their asthma well controlled, 81 (42.6%) had their asthma partly controlled, and 43 (22.6%) had uncontrolled asthma. Current smokers had uncontrolled asthma more often than ex-smokers, OR 2.54 (95% CI 1.25-5.14, p = 0.01). Patients with moderate to severe asthma exacerbation during the previous year had uncontrolled asthma more often than patients without an exacerbation, OR 2.17 (95% CI 1.06-4.47, p = 0.04), and patients with FEV1 80% of predicted, OR 2.04 (95% CI 1.02-4.08, p = 0.04). Conclusions Asthmatic patients with a clinically significant smoking history often do not have well controlled asthma. Poor asthma symptom control was associated with current smoking status, history of exacerbations and impaired lung function. Therefore, every attempt should be made to help asthmatics who smoke to quit smoking.Peer reviewe

Rakenteisten dokumenttien koostamismalli ja koostamisjärjestelmä SAW

Non peer reviewe

Remote Sensing methods for power line corridor surveys

AbstractTo secure uninterrupted distribution of electricity, effective monitoring and maintenance of power lines are needed. This literature review article aims to give a wide overview of the possibilities provided by modern remote sensing sensors in power line corridor surveys and to discuss the potential and limitations of different approaches. Monitoring of both power line components and vegetation around them is included. Remotely sensed data sources discussed in the review include synthetic aperture radar (SAR) images, optical satellite and aerial images, thermal images, airborne laser scanner (ALS) data, land-based mobile mapping data, and unmanned aerial vehicle (UAV) data. The review shows that most previous studies have concentrated on the mapping and analysis of network components. In particular, automated extraction of power line conductors has achieved much attention, and promising results have been reported. For example, accuracy levels above 90% have been presented for the extraction of conductors from ALS data or aerial images. However, in many studies datasets have been small and numerical quality analyses have been omitted. Mapping of vegetation near power lines has been a less common research topic than mapping of the components, but several studies have also been carried out in this field, especially using optical aerial and satellite images. Based on the review we conclude that in future research more attention should be given to an integrated use of various data sources to benefit from the various techniques in an optimal way. Knowledge in related fields, such as vegetation monitoring from ALS, SAR and optical image data should be better exploited to develop useful monitoring approaches. Special attention should be given to rapidly developing remote sensing techniques such as UAVs and laser scanning from airborne and land-based platforms. To demonstrate and verify the capabilities of automated monitoring approaches, large tests in various environments and practical monitoring conditions are needed. These should include careful quality analyses and comparisons between different data sources, methods and individual algorithms

Comparison of microalgae and rapeseed meal as supplementary protein in the grass silage based nutrition of dairy cows

Two experiments were conducted to evaluate microalgae as a protein supplement in the nutrition of lactating dairy cows in relation to unsupplemented and rapeseed meal supplemented diets. In both experiments multiparous Finnish Ayrshire cows were fed separately fixed amount of cereal-sugar beet pulp based concentrate (11 kg/d in Exp. 1 and 12 kg/d in Exp. 2), and grass silage ad libitum. In Exp. 1, six cows (212 days in milk; DIM) were used in a replicated 3 × 3 Latin square. Diets were supplemented isonitrogenously with rapeseed meal (pelleted rapeseed supplement, RSS), mixture of Spirulina platensis and Chlorella vulgaris microalgae (1:1 on dry matter (DM) basis; ALG) or a mixture of RSS and ALG (1:1 on crude protein (CP) basis; RSS-ALG). In Exp. 2, four intact cows and four rumen cannulated cows (190 DIM) were used in a replicated 4 × 4 Latin square. Treatments consisted of basal diet without protein supplement (NEG) or supplemented similarly as in Exp. 1 with the exception of RSS-ALG and ALG containing only S. platensis. Protein supplementation increased fibre and N digestibility but did not affect dry matter intake (DMI) or milk yield. The substitution of rapeseed by microalgae did not affect total DMI or milk yield in neither of the experiments, but changed the quality of DMI in Exp.2 by linearly decreasing concentrate:forage ratio of the diet due to poorer palatability of microalgae. The efficiency of N utilisation (NUE) in milk production varied from moderate (Exp. 1) to high (Exp. 2), and in Exp. 2 was decreased by both protein supplementation and microalgae inclusion in the diet. Protein supplementation or microalgae inclusion in the diet did not affect ruminal pH or major volatile fatty acids in Exp. 2, but both increased ruminal NH3-N concentration. There was likely a shortage of N for rumen microbes on NEG in Exp. 2 as indicated by low milk urea N and increased microbial N flow on protein supplemented diets. In both experiments, only minor differences were observed in plasma metabolites when microalgae substituted rapeseed. Even though arterial histidine concentrations were high, arterial histidine and carnosine concentrations (Exp. 1 and 2) and milk protein yields (Exp. 2) decreased by microalgae inclusion suggesting that histidine supply may become suboptimal on microalgae supplemented diets. Experiments demonstrated the suitability of microalgae as protein supplement for dairy cows, however, the protein value of microalgae is likely slightly lower than that of rapeseed meal.Two experiments were conducted to evaluate microalgae as a protein supplement in the nutrition of lactating dairy cows in relation to unsupplemented and rapeseed meal supplemented diets. In both experiments multiparous Finnish Ayrshire cows were fed separately fixed amount of cereal-sugar beet pulp based concentrate (11 kg/d in Exp. 1 and 12 kg/d in Exp. 2), and grass silage ad libitum. In Exp. 1, six cows (212 days in milk; DIM) were used in a replicated 3 × 3 Latin square. Diets were supplemented isonitrogenously with rapeseed meal (pelleted rapeseed supplement, RSS), mixture of Spirulina platensis and Chlorella vulgaris microalgae (1:1 on dry matter (DM) basis; ALG) or a mixture of RSS and ALG (1:1 on crude protein (CP) basis; RSS-ALG). In Exp. 2, four intact cows and four rumen cannulated cows (190 DIM) were used in a replicated 4 × 4 Latin square. Treatments consisted of basal diet without protein supplement (NEG) or supplemented similarly as in Exp. 1 with the exception of RSS-ALG and ALG containing only S. platensis. Protein supplementation increased fibre and N digestibility but did not affect dry matter intake (DMI) or milk yield. The substitution of rapeseed by microalgae did not affect total DMI or milk yield in neither of the experiments, but changed the quality of DMI in Exp.2 by linearly decreasing concentrate:forage ratio of the diet due to poorer palatability of microalgae. The efficiency of N utilisation (NUE) in milk production varied from moderate (Exp. 1) to high (Exp. 2), and in Exp. 2 was decreased by both protein supplementation and microalgae inclusion in the diet. Protein supplementation or microalgae inclusion in the diet did not affect ruminal pH or major volatile fatty acids in Exp. 2, but both increased ruminal NH3-N concentration. There was likely a shortage of N for rumen microbes on NEG in Exp. 2 as indicated by low milk urea N and increased microbial N flow on protein supplemented diets. In both experiments, only minor differences were observed in plasma metabolites when microalgae substituted rapeseed. Even though arterial histidine concentrations were high, arterial histidine and carnosine concentrations (Exp. 1 and 2) and milk protein yields (Exp. 2) decreased by microalgae inclusion suggesting that histidine supply may become suboptimal on microalgae supplemented diets. Experiments demonstrated the suitability of microalgae as protein supplement for dairy cows, however, the protein value of microalgae is likely slightly lower than that of rapeseed meal.Peer reviewe

Is field-measured tree height as reliable as believed A comparison study of tree height estimates from field measurement, airborne laser scanning and terrestrial laser scanning in a boreal forest

Quantitative comparisons of tree height observations from different sources are scarce due to the difficulties in effective sampling. In this study, the reliability and robustness of tree height observations obtained via a conventional field inventory, airborne laser scanning (ALS) and terrestrial laser scanning (TLS) were investigated. A carefully designed non-destructive experiment was conducted that included 1174 individual trees in 18 sample plots (32 m x 32 m) in a Scandinavian boreal forest. The point density of the ALS data was approximately 450 points/m(2). The TLS data were acquired with multi-scans from the center and the four quadrant directions of the sample plots. Both the ALS and TLS data represented the cutting edge point cloud products. Tree heights were manually measured from the ALS and TLS point clouds with the aid of existing tree maps. Therefore, the evaluation results revealed the capacities of the applied laser scanning (LS) data while excluding the influence of data processing approach such as the individual tree detection. The reliability and robustness of different tree height sources were evaluated through a cross-comparison of the ALS-, TLS-, and field- based tree heights. Compared to ALS and TLS, field measurements were more sensitive to stand complexity, crown classes, and species. Overall, field measurements tend to overestimate height of tall trees, especially tall trees in codominant crown class. In dense stands, high uncertainties also exist in the field measured heights for small trees in intermediate and suppressed crown class. The ALS-based tree height estimates were robust across all stand conditions. The taller the tree, the more reliable was the ALS-based tree height. The highest uncertainty in ALS-based tree heights came from trees in intermediate crown class, due to the difficulty of identifying treetops. When using TLS, reliable tree heights can be expected for trees lower than 15-20 m in height, depending on the complexity of forest stands. The advantage of LS systems was the robustness of the geometric accuracy of the data. The greatest challenges of the LS techniques in measuring individual tree heights lie in the occlusion effects, which lead to omissions of trees in intermediate and suppressed crown classes in ALS data and incomplete crowns of tall trees in TLS data.Peer reviewe

Improving distribution models of riparian vegetation with mobile laser scanning and hydraulic modelling

This study aimed at illustrating how direct measurements, mobile laser scanning and hydraulic modelling can be combined to quantify environmental drivers, improve vegetation models and increase our understanding of vegetation patterns in a sub-arctic river valley. Our results indicate that the resultant vegetation models successfully predict riparian vegetation patterns (Rho = 0.8 for total species richness, AUC = 0.97 for distribution) and highlight differences between eight functional species groups (Rho 0.46–0.84; AUC 0.79–0.93; functional group-specific effects). In our study setting, replacing the laser scanning-based and hydraulic modelling-based variables with a proxy variable elevation did not significantly weaken the models. However, using directly measured and modelled variables allows relating species patterns to e.g. stream power or the length of the flood-free period. Substituting these biologically relevant variables with proxies mask important processes and may reduce the transferability of the results into other sites. At the local scale, the amount of litter is a highly important driver of total species richness, distribution and abundance patterns (relative influences 49, 72 and 83%, respectively) and across all functional groups (13–57%; excluding lichen species richness) in the sub-arctic river valley. Moreover, soil organic matter and soil water content shape vegetation patterns (on average 16 and 7%, respectively). Fluvial disturbance is a key limiting factor only for lichen, bryophyte and dwarf shrub species in this environment (on average 37, 6 and 10%, respectively). Fluvial disturbance intensity is the most important component of disturbance for most functional groups while the length of the disturbance-free period is more relevant for lichens. We conclude that striving for as accurate quantifications of environmental drivers as possible may reveal important processes and functional group differences and help anticipate future changes in vegetation. Mobile laser scanning, high-resolution digital elevation models and hydraulic modelling offer useful methodology for improving correlative vegetation models.</p

Area-Based Approach for Mapping and Monitoring Riverine Vegetation Using Mobile Laser Scanning

Peer reviewe

Advances in Forest Inventory Using Airborne Laser Scanning

Peer reviewe

Airborne Laser Scanning Outperforms the Alternative 3D Techniques in Capturing Variation in Tree Height and Forest Density in Southern Boreal Forests

The objective of this study is to better understand the relationship between forest structure and point cloud features generated from certain airborne and space borne sensors. Point cloud features derived from airborne laser scanning (ALS), aerial imagery (AI), WorldView-2 imagery (WV2), TerraSAR-X, and Tandem-X (TDX) data were classified as features characterizing forest height and density as well as variation in tree height. Correlations between these features and field-measured attributes describing forest height, density and tree height variation were investigated at plot scale. From the field-measured attributes, basal area (G) and the number of trees per unit area (N) were used as forest density indicators whereas maximum tree height (H-max) and standard deviation in tree height (H-std) were used as indicators for forest height and tree height variation, respectively. In the analyses, field observations from 91 sample plots (32 m x 32 m) located in southern Finland were used. Even though ALS was found to be the most accurate data source in characterizing forest structure, AI, WV2, and TDX were also capable of characterizing forest height at plot scale with correlation coefficients stronger than 0.85. However, ALS was the only data source capable of providing separate features for characterizing also the variation in tree height and forest density. Features related to forest height, generated from the other data sources besides ALS, also provided strongest correlation with the forest density attributes and variation in tree height, in addition to H-max. Due to these more diverse characterization capabilities, forest structural attributes can be predicted more accurately by using ALS, also in the areas where the relation between the attributes of interest is not solely dependent on forest height, compared to the other investigated 3D remote sensing data sources.Peer reviewe